The present invention relates to processing information. In particular, the present invention relates to accessing and ranking definitions of terms.
Definitions include a statement of the meanings of words, phrases and terms and thus are useful information. Searching and finding relevant definitions can be cumbersome and difficult. In some situations, a large number of descriptions related to a term can be accessed, for example using the Internet. In other situations, for example on a company intranet, few descriptions of terms may exist. In either case, it can be cumbersome to manually search through results to find a relevant, useful definition for a term.
A traditional information retrieval process is designed to search for entire relevant documents given an input query, and thus is not suitable for providing useful definitions. Other processes, given questions of “what is X” or “who is X”, extract answers from multiple documents and combine the extracted answers into a single unified answer. This process of question/answering can be a means of helping people find definitions. However, the process is difficult to realize in practice. Usually definitions extracted from different documents describe terms from different perspectives, and thus are not suitable for combination.
Additionally, methods for extracting definitions from documents have also been proposed in text mining applications. These methods resort to human-defined rules for definition extraction. The rules can provide relevant definitions, but also can result in a large amount of information that a user will need to look through to find relevant information. As a result, there is a need to provide relevant definitions to a user in a more efficient, useful manner.